{"title":"A method for automatic generation of a fuzzy model","authors":"J. Yen, H. Wang, J. Liao","doi":"10.1109/IFIS.1993.324208","DOIUrl":null,"url":null,"abstract":"The goal of this research is to develop a method to automate the process of fuzzy model construction. The method we developed extends the existing methods and is based on a combination of genetic algorithms and statistic techniques. The preliminary testing shows that it has the advantages of implementation simplicity, a short training cycle and simple resulting fuzzy model.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IFIS.1993.324208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The goal of this research is to develop a method to automate the process of fuzzy model construction. The method we developed extends the existing methods and is based on a combination of genetic algorithms and statistic techniques. The preliminary testing shows that it has the advantages of implementation simplicity, a short training cycle and simple resulting fuzzy model.<>